Firstly to explain the situation I have to deal with in more depth:

I have a dataset for which part of the features (columns of data) are identical from observation to observation (rows) and another part of the features are variable. Roughly every 1-200 observations have some features that fall into the pattern described, whereas the dataset is very large.

Firstly, are there any specific reason why a neural network with above data would fail? Any papers/information/ideas that describe how to deal with this kind of situation?

Thanks